from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HpMatchReporting(other_library="sklearnex", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | library | diff_accuracy_scores | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4 | KNeighborsClassifier_brute_force | sklearn | 0.067 | predict | 100000 | 1000 | 100 | 2.854584 | 0.035681 | NaN | 0.000280 | 0.002855 | brute | -1 | 5 | 0.743 | 0.172763 | 0.001154 | 0.676 | 16.523125 | 16.523493 |
| 5 | KNeighborsClassifier_brute_force | sklearn | 1.000 | predict | 100000 | 1 | 100 | 0.023703 | 0.003192 | NaN | 0.000034 | 0.023703 | brute | -1 | 5 | 1.000 | 0.008614 | 0.000261 | 0.000 | 2.751600 | 2.752866 |
| 7 | KNeighborsClassifier_brute_force | sklearn | 0.103 | predict | 100000 | 1000 | 100 | 2.093583 | 0.001914 | NaN | 0.000382 | 0.002094 | brute | 1 | 100 | 0.846 | 0.175009 | 0.000722 | 0.743 | 11.962707 | 11.962809 |
| 13 | KNeighborsClassifier_brute_force | sklearn | 0.103 | predict | 100000 | 1000 | 100 | 2.097554 | 0.011044 | NaN | 0.000381 | 0.002098 | brute | 1 | 5 | 0.743 | 0.209593 | 0.000434 | 0.846 | 10.007766 | 10.007788 |
| 16 | KNeighborsClassifier_brute_force | sklearn | 0.067 | predict | 100000 | 1000 | 100 | 1.172756 | 0.005058 | NaN | 0.000682 | 0.001173 | brute | 1 | 1 | 0.676 | 0.173695 | 0.000380 | 0.743 | 6.751800 | 6.751816 |
| 17 | KNeighborsClassifier_brute_force | sklearn | 1.000 | predict | 100000 | 1 | 100 | 0.018287 | 0.000186 | NaN | 0.000044 | 0.018287 | brute | 1 | 1 | 0.000 | 0.008849 | 0.000289 | 1.000 | 2.066672 | 2.067776 |
| 22 | KNeighborsClassifier_brute_force | sklearn | 0.038 | predict | 100000 | 1000 | 2 | 2.783096 | 0.015087 | NaN | 0.000006 | 0.002783 | brute | -1 | 5 | 0.883 | 0.025507 | 0.000160 | 0.845 | 109.109544 | 109.111688 |
| 25 | KNeighborsClassifier_brute_force | sklearn | 0.004 | predict | 100000 | 1000 | 2 | 2.062517 | 0.004221 | NaN | 0.000008 | 0.002063 | brute | 1 | 100 | 0.887 | 0.026660 | 0.000170 | 0.883 | 77.364249 | 77.365823 |
| 31 | KNeighborsClassifier_brute_force | sklearn | 0.004 | predict | 100000 | 1000 | 2 | 2.045558 | 0.002533 | NaN | 0.000008 | 0.002046 | brute | 1 | 5 | 0.883 | 0.059798 | 0.000219 | 0.887 | 34.207766 | 34.207996 |
| 34 | KNeighborsClassifier_brute_force | sklearn | 0.038 | predict | 100000 | 1000 | 2 | 1.056716 | 0.002134 | NaN | 0.000015 | 0.001057 | brute | 1 | 1 | 0.845 | 0.026695 | 0.000103 | 0.883 | 39.585345 | 39.585640 |
fit
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | 7.165 | 0.0 | -1 | 1 | 0.047 | 0.0 | 0.235 | 0.235 | See | See |
| 3 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | 7.208 | 0.0 | -1 | 5 | 0.047 | 0.0 | 0.234 | 0.234 | See | See |
| 6 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | 7.341 | 0.0 | 1 | 100 | 0.047 | 0.0 | 0.232 | 0.232 | See | See |
| 9 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | 7.313 | 0.0 | -1 | 100 | 0.047 | 0.0 | 0.235 | 0.235 | See | See |
| 12 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | 7.150 | 0.0 | 1 | 5 | 0.047 | 0.0 | 0.239 | 0.239 | See | See |
| 15 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 100 | 0.011 | 0.0 | 7.262 | 0.0 | 1 | 1 | 0.047 | 0.0 | 0.234 | 0.234 | See | See |
| 18 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.369 | 0.0 | -1 | 1 | 0.008 | 0.0 | 0.527 | 0.528 | See | See |
| 21 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.378 | 0.0 | -1 | 5 | 0.008 | 0.0 | 0.518 | 0.518 | See | See |
| 24 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.378 | 0.0 | 1 | 100 | 0.008 | 0.0 | 0.520 | 0.521 | See | See |
| 27 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.377 | 0.0 | -1 | 100 | 0.008 | 0.0 | 0.518 | 0.518 | See | See |
| 30 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.376 | 0.0 | 1 | 5 | 0.008 | 0.0 | 0.521 | 0.521 | See | See |
| 33 | KNeighborsClassifier_brute_force | sklearn | fit | 100000 | 100000 | 2 | 0.004 | 0.0 | 0.373 | 0.0 | 1 | 1 | 0.008 | 0.0 | 0.521 | 0.522 | See | See |
predict
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 100 | 1.944 | 0.052 | 0.000 | 0.002 | -1 | 1 | 0.174 | 0.001 | 11.159 | 11.159 | See | See |
| 2 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 100 | 0.023 | 0.003 | 0.000 | 0.023 | -1 | 1 | 0.009 | 0.000 | 2.691 | 2.693 | See | See |
| 4 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 100 | 2.855 | 0.036 | 0.000 | 0.003 | -1 | 5 | 0.173 | 0.001 | 16.523 | 16.523 | See | See |
| 5 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 100 | 0.024 | 0.003 | 0.000 | 0.024 | -1 | 5 | 0.009 | 0.000 | 2.752 | 2.753 | See | See |
| 7 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 100 | 2.094 | 0.002 | 0.000 | 0.002 | 1 | 100 | 0.175 | 0.001 | 11.963 | 11.963 | See | See |
| 8 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 100 | 0.019 | 0.000 | 0.000 | 0.019 | 1 | 100 | 0.008 | 0.000 | 2.253 | 2.255 | See | See |
| 10 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 100 | 2.910 | 0.037 | 0.000 | 0.003 | -1 | 100 | 0.209 | 0.001 | 13.935 | 13.936 | See | See |
| 11 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 100 | 0.024 | 0.002 | 0.000 | 0.024 | -1 | 100 | 0.009 | 0.000 | 2.721 | 2.723 | See | See |
| 13 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 100 | 2.098 | 0.011 | 0.000 | 0.002 | 1 | 5 | 0.210 | 0.000 | 10.008 | 10.008 | See | See |
| 14 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 100 | 0.019 | 0.000 | 0.000 | 0.019 | 1 | 5 | 0.009 | 0.000 | 2.268 | 2.269 | See | See |
| 16 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 100 | 1.173 | 0.005 | 0.001 | 0.001 | 1 | 1 | 0.174 | 0.000 | 6.752 | 6.752 | See | See |
| 17 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 100 | 0.018 | 0.000 | 0.000 | 0.018 | 1 | 1 | 0.009 | 0.000 | 2.067 | 2.068 | See | See |
| 19 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 2 | 1.789 | 0.027 | 0.000 | 0.002 | -1 | 1 | 0.025 | 0.000 | 70.198 | 70.202 | See | See |
| 20 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 2 | 0.007 | 0.003 | 0.000 | 0.007 | -1 | 1 | 0.001 | 0.000 | 9.583 | 9.741 | See | See |
| 22 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 2 | 2.783 | 0.015 | 0.000 | 0.003 | -1 | 5 | 0.026 | 0.000 | 109.110 | 109.112 | See | See |
| 23 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 2 | 0.009 | 0.002 | 0.000 | 0.009 | -1 | 5 | 0.001 | 0.000 | 11.797 | 12.031 | See | See |
| 25 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 2 | 2.063 | 0.004 | 0.000 | 0.002 | 1 | 100 | 0.027 | 0.000 | 77.364 | 77.366 | See | See |
| 26 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 100 | 0.001 | 0.000 | 3.936 | 4.027 | See | See |
| 28 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 2 | 2.797 | 0.028 | 0.000 | 0.003 | -1 | 100 | 0.060 | 0.000 | 46.850 | 46.850 | See | See |
| 29 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 2 | 0.009 | 0.002 | 0.000 | 0.009 | -1 | 100 | 0.001 | 0.000 | 11.359 | 11.575 | See | See |
| 31 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 2 | 2.046 | 0.003 | 0.000 | 0.002 | 1 | 5 | 0.060 | 0.000 | 34.208 | 34.208 | See | See |
| 32 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 5 | 0.001 | 0.000 | 3.569 | 3.632 | See | See |
| 34 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1000 | 2 | 1.057 | 0.002 | 0.000 | 0.001 | 1 | 1 | 0.027 | 0.000 | 39.585 | 39.586 | See | See |
| 35 | KNeighborsClassifier_brute_force | sklearn | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 0.001 | 0.000 | 2.470 | 2.519 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | library | diff_accuracy_scores | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | sklearn | 0.011 | predict | 1000000 | 1000 | 10 | 1.701493 | 0.008678 | NaN | 0.000047 | 0.001701 | kd_tree | 1 | 5 | 0.975 | 0.116527 | 0.001456 | 0.964 | 14.601746 | 14.602887 |
| 4 | KNeighborsClassifier_kd_tree | sklearn | 0.002 | predict | 1000000 | 1000 | 10 | 0.950790 | 0.006334 | NaN | 0.000084 | 0.000951 | kd_tree | -1 | 5 | 0.975 | 0.599678 | 0.013020 | 0.973 | 1.585500 | 1.585874 |
| 10 | KNeighborsClassifier_kd_tree | sklearn | 0.011 | predict | 1000000 | 1000 | 10 | 0.903230 | 0.004839 | NaN | 0.000089 | 0.000903 | kd_tree | 1 | 1 | 0.964 | 0.203214 | 0.002935 | 0.975 | 4.444735 | 4.445199 |
| 13 | KNeighborsClassifier_kd_tree | sklearn | 0.002 | predict | 1000000 | 1000 | 10 | 5.397381 | 0.102031 | NaN | 0.000015 | 0.005397 | kd_tree | 1 | 100 | 0.973 | 0.205844 | 0.001802 | 0.975 | 26.220706 | 26.221711 |
| 19 | KNeighborsClassifier_kd_tree | sklearn | 0.028 | predict | 1000 | 1000 | 2 | 0.020273 | 0.000212 | NaN | 0.000789 | 0.000020 | kd_tree | 1 | 5 | 0.923 | 0.000489 | 0.000124 | 0.895 | 41.490814 | 42.806381 |
| 22 | KNeighborsClassifier_kd_tree | sklearn | 0.004 | predict | 1000 | 1000 | 2 | 0.022752 | 0.000471 | NaN | 0.000703 | 0.000023 | kd_tree | -1 | 5 | 0.923 | 0.004568 | 0.000212 | 0.919 | 4.980863 | 4.986206 |
| 28 | KNeighborsClassifier_kd_tree | sklearn | 0.028 | predict | 1000 | 1000 | 2 | 0.019136 | 0.000230 | NaN | 0.000836 | 0.000019 | kd_tree | 1 | 1 | 0.895 | 0.000743 | 0.000121 | 0.923 | 25.751095 | 26.090725 |
| 31 | KNeighborsClassifier_kd_tree | sklearn | 0.004 | predict | 1000 | 1000 | 2 | 0.033771 | 0.000218 | NaN | 0.000474 | 0.000034 | kd_tree | 1 | 100 | 0.919 | 0.000778 | 0.000161 | 0.923 | 43.387250 | 44.303833 |
fit
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000000 | 1000000 | 10 | 3.048 | 0.072 | 0.026 | 0.0 | 1 | 5 | 0.757 | 0.004 | 4.025 | 4.025 | See | See |
| 3 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000000 | 1000000 | 10 | 3.900 | 0.025 | 0.021 | 0.0 | -1 | 5 | 0.735 | 0.006 | 5.305 | 5.305 | See | See |
| 6 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000000 | 1000000 | 10 | 4.042 | 0.044 | 0.020 | 0.0 | -1 | 1 | 0.756 | 0.008 | 5.348 | 5.348 | See | See |
| 9 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000000 | 1000000 | 10 | 4.103 | 0.099 | 0.019 | 0.0 | 1 | 1 | 0.715 | 0.004 | 5.735 | 5.736 | See | See |
| 12 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000000 | 1000000 | 10 | 4.141 | 0.022 | 0.019 | 0.0 | 1 | 100 | 0.764 | 0.005 | 5.420 | 5.420 | See | See |
| 15 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000000 | 1000000 | 10 | 3.587 | 0.060 | 0.022 | 0.0 | -1 | 100 | 0.736 | 0.015 | 4.873 | 4.874 | See | See |
| 18 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.028 | 0.0 | 1 | 5 | 0.004 | 0.001 | 0.151 | 0.163 | See | See |
| 21 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.030 | 0.0 | -1 | 5 | 0.002 | 0.001 | 0.346 | 0.445 | See | See |
| 24 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.030 | 0.0 | -1 | 1 | 0.001 | 0.000 | 0.615 | 0.624 | See | See |
| 27 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.030 | 0.0 | 1 | 1 | 0.001 | 0.000 | 0.598 | 0.607 | See | See |
| 30 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.030 | 0.0 | 1 | 100 | 0.001 | 0.000 | 0.602 | 0.611 | See | See |
| 33 | KNeighborsClassifier_kd_tree | sklearn | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.030 | 0.0 | -1 | 100 | 0.001 | 0.000 | 0.622 | 0.631 | See | See |
predict
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1000 | 10 | 1.701 | 0.009 | 0.000 | 0.002 | 1 | 5 | 0.117 | 0.001 | 14.602 | 14.603 | See | See |
| 2 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 0.000 | 0.000 | 5.789 | 6.504 | See | See |
| 4 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1000 | 10 | 0.951 | 0.006 | 0.000 | 0.001 | -1 | 5 | 0.600 | 0.013 | 1.586 | 1.586 | See | See |
| 5 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 5 | 0.001 | 0.000 | 5.866 | 6.455 | See | See |
| 7 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1000 | 10 | 0.505 | 0.012 | 0.000 | 0.001 | -1 | 1 | 0.121 | 0.002 | 4.187 | 4.188 | See | See |
| 8 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 12.022 | 13.583 | See | See |
| 10 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1000 | 10 | 0.903 | 0.005 | 0.000 | 0.001 | 1 | 1 | 0.203 | 0.003 | 4.445 | 4.445 | See | See |
| 11 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 4.397 | 4.886 | See | See |
| 13 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1000 | 10 | 5.397 | 0.102 | 0.000 | 0.005 | 1 | 100 | 0.206 | 0.002 | 26.221 | 26.222 | See | See |
| 14 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | 1 | 100 | 0.000 | 0.000 | 10.193 | 11.325 | See | See |
| 16 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1000 | 10 | 3.209 | 0.028 | 0.000 | 0.003 | -1 | 100 | 0.592 | 0.005 | 5.419 | 5.419 | See | See |
| 17 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000000 | 1 | 10 | 0.005 | 0.001 | 0.000 | 0.005 | -1 | 100 | 0.001 | 0.000 | 8.590 | 9.440 | See | See |
| 19 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1000 | 2 | 0.020 | 0.000 | 0.001 | 0.000 | 1 | 5 | 0.000 | 0.000 | 41.491 | 42.806 | See | See |
| 20 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 0.000 | 0.000 | 5.301 | 7.023 | See | See |
| 22 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1000 | 2 | 0.023 | 0.000 | 0.001 | 0.000 | -1 | 5 | 0.005 | 0.000 | 4.981 | 4.986 | See | See |
| 23 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 0.000 | 0.000 | 16.918 | 21.755 | See | See |
| 25 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1000 | 2 | 0.021 | 0.001 | 0.001 | 0.000 | -1 | 1 | 0.000 | 0.000 | 44.022 | 45.824 | See | See |
| 26 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 1 | 0.000 | 0.000 | 17.001 | 21.526 | See | See |
| 28 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1000 | 2 | 0.019 | 0.000 | 0.001 | 0.000 | 1 | 1 | 0.001 | 0.000 | 25.751 | 26.091 | See | See |
| 29 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 5.210 | 7.022 | See | See |
| 31 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1000 | 2 | 0.034 | 0.000 | 0.000 | 0.000 | 1 | 100 | 0.001 | 0.000 | 43.387 | 44.304 | See | See |
| 32 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 0.000 | 0.000 | 5.202 | 6.759 | See | See |
| 34 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1000 | 2 | 0.036 | 0.005 | 0.000 | 0.000 | -1 | 100 | 0.005 | 0.000 | 7.759 | 7.778 | See | See |
| 35 | KNeighborsClassifier_kd_tree | sklearn | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 100 | 0.000 | 0.000 | 17.681 | 22.543 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
fit
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | sklearn | fit | 1000000 | 1000000 | 2 | 0.567 | 0.006 | 30 | 0.028 | 0.0 | k-means++ | 0.407 | 0.029 | 1.393 | 1.396 | See | See |
| 3 | KMeans_tall | sklearn | fit | 1000000 | 1000000 | 2 | 0.504 | 0.008 | 30 | 0.032 | 0.0 | random | 0.367 | 0.019 | 1.371 | 1.373 | See | See |
| 6 | KMeans_tall | sklearn | fit | 1000000 | 1000000 | 100 | 5.765 | 0.023 | 30 | 0.139 | 0.0 | k-means++ | 2.775 | 0.011 | 2.077 | 2.077 | See | See |
| 9 | KMeans_tall | sklearn | fit | 1000000 | 1000000 | 100 | 5.516 | 0.022 | 30 | 0.145 | 0.0 | random | 2.718 | 0.059 | 2.029 | 2.030 | See | See |
predict
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | sklearn | predict | 1000000 | 1000 | 2 | 0.002 | 0.0 | 30 | 0.011 | 0.000 | k-means++ | 0.0 | 0.0 | 10.532 | 13.013 | See | See |
| 2 | KMeans_tall | sklearn | predict | 1000000 | 1 | 2 | 0.001 | 0.0 | 30 | 0.000 | 0.001 | k-means++ | 0.0 | 0.0 | 11.065 | 14.109 | See | See |
| 4 | KMeans_tall | sklearn | predict | 1000000 | 1000 | 2 | 0.001 | 0.0 | 30 | 0.012 | 0.000 | random | 0.0 | 0.0 | 9.471 | 11.468 | See | See |
| 5 | KMeans_tall | sklearn | predict | 1000000 | 1 | 2 | 0.001 | 0.0 | 30 | 0.000 | 0.001 | random | 0.0 | 0.0 | 10.662 | 13.261 | See | See |
| 7 | KMeans_tall | sklearn | predict | 1000000 | 1000 | 100 | 0.002 | 0.0 | 30 | 0.485 | 0.000 | k-means++ | 0.0 | 0.0 | 6.115 | 6.803 | See | See |
| 8 | KMeans_tall | sklearn | predict | 1000000 | 1 | 100 | 0.001 | 0.0 | 30 | 0.001 | 0.001 | k-means++ | 0.0 | 0.0 | 10.677 | 13.511 | See | See |
| 10 | KMeans_tall | sklearn | predict | 1000000 | 1000 | 100 | 0.002 | 0.0 | 30 | 0.486 | 0.000 | random | 0.0 | 0.0 | 6.103 | 6.800 | See | See |
| 11 | KMeans_tall | sklearn | predict | 1000000 | 1 | 100 | 0.001 | 0.0 | 30 | 0.001 | 0.001 | random | 0.0 | 0.0 | 10.727 | 13.577 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | library | diff_adjusted_rand_scores | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | init | max_iter | n_clusters | n_init | tol | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4 | KMeans_short | sklearn | 0.001361 | predict | 10000 | 1000 | 2 | 0.001827 | 0.000184 | 20 | 0.008757 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.000744 | 0.000502 | 0.000100 | -0.000617 | 3.642602 | 3.713657 |
| 7 | KMeans_short | sklearn | 0.002111 | predict | 10000 | 1000 | 100 | 0.002515 | 0.000278 | 20 | 0.318138 | 0.000003 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.340206 | 0.000996 | 0.000154 | 0.342317 | 2.525393 | 2.555525 |
| 10 | KMeans_short | sklearn | 0.016992 | predict | 10000 | 1000 | 100 | 0.002498 | 0.000259 | 20 | 0.320238 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.321348 | 0.001018 | 0.000152 | 0.338339 | 2.453443 | 2.480801 |
fit
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | sklearn | fit | 10000 | 10000 | 2 | 0.072 | 0.000 | 20 | 0.002 | 0.0 | random | 0.026 | 0.001 | 2.786 | 2.789 | See | See |
| 3 | KMeans_short | sklearn | fit | 10000 | 10000 | 2 | 0.209 | 0.000 | 20 | 0.001 | 0.0 | k-means++ | 0.081 | 0.001 | 2.580 | 2.581 | See | See |
| 6 | KMeans_short | sklearn | fit | 10000 | 10000 | 100 | 0.191 | 0.001 | 20 | 0.042 | 0.0 | random | 0.105 | 0.002 | 1.816 | 1.816 | See | See |
| 9 | KMeans_short | sklearn | fit | 10000 | 10000 | 100 | 0.556 | 0.004 | 20 | 0.014 | 0.0 | k-means++ | 0.312 | 0.009 | 1.784 | 1.785 | See | See |
predict
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | sklearn | predict | 10000 | 1000 | 2 | 0.002 | 0.001 | 20 | 0.008 | 0.000 | random | 0.000 | 0.0 | 4.137 | 4.207 | See | See |
| 2 | KMeans_short | sklearn | predict | 10000 | 1 | 2 | 0.001 | 0.000 | 20 | 0.000 | 0.001 | random | 0.000 | 0.0 | 10.228 | 12.475 | See | See |
| 4 | KMeans_short | sklearn | predict | 10000 | 1000 | 2 | 0.002 | 0.000 | 20 | 0.009 | 0.000 | k-means++ | 0.001 | 0.0 | 3.643 | 3.714 | See | See |
| 5 | KMeans_short | sklearn | predict | 10000 | 1 | 2 | 0.001 | 0.000 | 20 | 0.000 | 0.001 | k-means++ | 0.000 | 0.0 | 10.631 | 13.075 | See | See |
| 7 | KMeans_short | sklearn | predict | 10000 | 1000 | 100 | 0.003 | 0.000 | 20 | 0.318 | 0.000 | random | 0.001 | 0.0 | 2.525 | 2.556 | See | See |
| 8 | KMeans_short | sklearn | predict | 10000 | 1 | 100 | 0.001 | 0.000 | 20 | 0.001 | 0.001 | random | 0.000 | 0.0 | 8.577 | 9.967 | See | See |
| 10 | KMeans_short | sklearn | predict | 10000 | 1000 | 100 | 0.002 | 0.000 | 20 | 0.320 | 0.000 | k-means++ | 0.001 | 0.0 | 2.453 | 2.481 | See | See |
| 11 | KMeans_short | sklearn | predict | 10000 | 1 | 100 | 0.001 | 0.000 | 20 | 0.001 | 0.001 | k-means++ | 0.000 | 0.0 | 8.713 | 10.018 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
fit
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | sklearn | fit | 1000000 | 1000000 | 100 | 10.792 | 0.062 | [20] | 0.074 | 0.000 | 1.942 | 0.010 | 5.557 | 5.557 | See | See |
| 3 | LogisticRegression | sklearn | fit | 1000 | 1000 | 10000 | 0.785 | 0.022 | [27] | 0.102 | 0.001 | 0.957 | 0.031 | 0.820 | 0.821 | See | See |
predict
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | sklearn | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | [20] | 2.806 | 0.0 | 0.000 | 0.0 | 0.829 | 0.915 | See | See |
| 2 | LogisticRegression | sklearn | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | [20] | 0.012 | 0.0 | 0.000 | 0.0 | 0.376 | 0.441 | See | See |
| 4 | LogisticRegression | sklearn | predict | 1000 | 100 | 10000 | 0.002 | 0.0 | [27] | 5.080 | 0.0 | 0.003 | 0.0 | 0.539 | 0.546 | See | See |
| 5 | LogisticRegression | sklearn | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | [27] | 0.913 | 0.0 | 0.001 | 0.0 | 0.128 | 0.132 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
fit
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | sklearn | fit | 1000 | 1000 | 10000 | 0.158 | 0.001 | 0.506 | 0.0 | 0.180 | 0.010 | 0.877 | 0.878 | See | See |
| 3 | Ridge | sklearn | fit | 1000000 | 1000000 | 100 | 1.063 | 0.010 | 0.752 | 0.0 | 0.217 | 0.001 | 4.896 | 4.896 | See | See |
predict
| estimator | library | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | sklearn | predict | 1000 | 1000 | 10000 | 0.012 | 0.0 | 6.746 | 0.0 | 0.019 | 0.0 | 0.611 | 0.611 | See | See |
| 2 | Ridge | sklearn | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | 1.002 | 0.0 | 0.000 | 0.0 | 0.732 | 0.889 | See | See |
| 4 | Ridge | sklearn | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | 5.515 | 0.0 | 0.000 | 0.0 | 0.608 | 0.732 | See | See |
| 5 | Ridge | sklearn | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | 0.013 | 0.0 | 0.000 | 0.0 | 0.655 | 0.812 | See | See |